부산대학교 도서관

Abstract Background Acinetobacter baumannii has emerged as one of the common multidrug resistance pathogens causing hospital-acquired infections. This study was conducted to elucidate the distribution of antimicrobial resistance genes in the bacterial population in Thailand. Multidrug-resistant A. baumannii (MDR A. baumannii) isolates were characterized phenotypically, and the molecular epidemiology of clinical isolates in 11 tertiary hospitals was investigated at a country-wide level. Methods A total of 135 nonrepetitive MDR A. baumannii isolates collected from tertiary care hospitals across 5 regions of Thailand were examined for antibiotic susceptibility, resistance genes, and sequence types. Multilocus sequence typing (MLST) was performed to characterize the spread of regional lineages. Results ST2 belonging to IC2 was the most dominant sequence type in Thailand (65.19%), and to a lesser extent, there was also evidence of the spread of ST164 (10.37%), ST129 (3.70%), ST16 (2.96%), ST98 (2.96%), ST25 (2.96%), ST215 (2.22%), ST338 (1.48%), and ST745 (1.48%). The novel sequence types ST1551, ST1552, ST1553, and ST1557 were also identified in this study. Among these, the blaoxa-23 gene was by far the most widespread in MDR A. baumannii, while the blaoxa-24/40 and blaoxa-58 genes appeared to be less dominant in this region. The results demonstrated that the predominant class D carbapenemase was blaOXA-23, followed by the class B carbapenemase blaNDM-like, while the mcr-1 gene was not observed in any isolate. Most of the MDR A. baumannii isolates were resistant to ceftazidime (99.23%), gentamicin (91.85%), amikacin (82.96%), and ciprofloxacin (97.78%), while all of them were resistant to carbapenems. The results suggested that colistin could still be effective against MDR A. baumannii in this region. Conclusion This is the first molecular epidemiological analysis of MDR A. baumannii clinical isolates at the national level in Thailand to date. Studies on the clonal relatedness of MDR A. baumannii isolates could generate useful data to understand the local epidemiology and international comparisons of nosocomial outbreaks.